Julian Michael

Julian Michael

I am a 3rd-year graduate student at the Paul G. Allen School of Computer Science and Engineering at the University of Washington. I am advised by Luke Zettlemoyer and I am a member of UW NLP.

My research is on formal semantics of natural language — in particular, how to design, annotate, and model semantics in a scalable, data-driven way while taking advantage of our understanding of linguistic structure. I have worked on approaches to crowdsourcing annotation for syntactic parsing, semantic role labeling, and predicate-argument structure.

You can find me on Github or email: julianjm (at) cs.washington.edu.

Conference Publications

Large-Scale QA-SRL Parsing
Nicholas Fitzgerald, Julian Michael, Luheng He, and Luke Zettlemoyer
ACL 2018
Bib

Crowdsourcing Question-Answer Meaning Representations
Julian Michael, Gabriel Stanovsky, Luheng He, Ido Dagan, and Luke Zettlemoyer
NAACL 2018
Code Data Bib
ArXiv long version (Nov 2017) PDF Bib

Supervised Open Information Extraction
Gabriel Stanovsky, Julian Michael, Luke Zettlemoyer, and Ido Dagan
NAACL 2018
Bib

Human-in-the-Loop Parsing
Luheng He, Julian Michael, Mike Lewis, and Luke Zettlemoyer
EMNLP 2016
S2 PDF Code Slides Bib

Proving Infinitary Formulas
Amelia Harrison, Vladimir Lifschitz, and Julian Michael
TPLP Vol. 16, 5-6; Presented at ICLP 2016
S2 PDF Bib
ASPOCP version (Aug 2015) S2 PDF Bib


Other Publications

GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman
ArXiv preprint, Apr 2018
PDF

The Theory of Correlation Formulas and their Application to Discourse Coherence
Julian Michael
Undergraduate Honors Thesis, UT Austin, 2015
S2 PDF Bib

The Winograd Schema Challenge and Reasoning about Correlation
Daniel Bailey, Amelia Harrison, Yuliya Lierler, Vladimir Lifschitz, and Julian Michael
Commonsense 2015
S2 PDF Bib


Collaborators